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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3

Cluster Variation Method Analysis of Correlations and Entropy in BCC Solid Solutions

Solid solutions occur when multiple chemical species share sites of a common crystal lattice. Although the single site occupation is random, chemical interaction preferences bias the occupation probabilities of neighboring sites, and this bias reduced the entropy of mixing below its ideal value. Sufficiently strong bias leads to symmetry-breaking phase transitions. Here, we apply the cluster variation method to explore solid solutions on body centered cubic lattices in the context of two specific compounds that exhibit opposite ordering trends. Employing density functional theory to model the energetics, we show that CuZn exhibits an order-disorder transition to the CsCl prototype structure, while AlLi instead takes the NaTl prototype structure, and we evaluate their temperature-dependent order parameters, correlations and entropies.

36 MATERIALS SCIENCE↗

Direct observation of a dynamical glass transition in a nanomagnetic artificial Hopfield network

Spin glasses, generally defined as disordered systems with randomized competing interactions, are a widely investigated complex system. Theoretical models describing spin glasses are broadly used in other complex systems, such as those describing brain function, error-correcting codes5 or stock-market dynamics. This wide interest in spin glasses provides strong motivation to generate an artificial spin glass within the framework of artificial spin ice systems. Here we present the experimental realization of an artificial spin glass consisting of dipolar coupled single-domain Ising-type nanomagnets arranged onto an interaction network that replicates the aspects of a Hopfield neural network. Using cryogenic X-ray photoemission electron microscopy (XPEEM), we performed temperature-dependent imaging of thermally driven moment fluctuations within these networks and observed characteristic features of a two-dimensional Ising spin glass. Specifically, the temperature dependence of the spin glass correlation function follows a power-law trend predicted from theoretical models on two-dimensional spin glasses. As a result, we observe clear signatures of the hard-to-observe rugged spin glass free energy in the form of sub-aging, out-of-equilibrium autocorrelations and a transition from stable to unstable dynamics.

36 MATERIALS SCIENCE↗

Melting, reentrant ordering and peak effect for Wigner crystals with quenched and thermal disorder

Abstract We consider simulations of Wigner crystals in solid state systems interacting with random quenched disorder in the presence of thermal fluctuations. When quenched disorder is absent, there is a well defined melting temperature determined by the proliferation of topological defects, while for zero temperature, there is a critical quenched disorder strength above which topological defects proliferate. When both thermal and quenched disorder are present, these effects compete, and the thermal fluctuations can reduce the effectiveness of the quenched disorder, leading to a reentrant ordered phase in agreement with the predictions of Nelson (1983 Phys. Rev. B 27 2902–14). There are two competing theories for the low temperature behavior, and our simulations show that both capture aspects of the actual response. The critical disorder strength separating ordered from disordered states remains finite as the temperature goes to zero, as predicted by Cha and Fertig (1995 Phys. Rev. Lett. 74 4867–70), instead of dropping to zero as predicted by Nelson. At the same time, the critical disorder strength decreases with decreasing temperature, as predicted by Nelson, instead of remaining constant, as predicted by Cha and Fertig. The onset of the reentrant phase can be deduced based on changes in the transport response, where the reentrant ordering appears as an increase in the mobility or the occurrence of a depinning transition. We also find that when the system is in the ordered state and thermally melts, there is an increase in the effective damping or pinning. This produces a drop in the electron mobility that is similar to the peak effect phenomenon found in superconducting vortices, where thermal effects soften the lattice or break down its elasticity, allowing the particles to better adjust their positions to take full advantage of the quenched disorder.

36 MATERIALS SCIENCE↗

Nonlinear dynamics, avalanches, and noise for driven Wigner crystals

Here we consider the driven dynamics of Wigner crystals interacting with random disorder. Using numerical simulations, we find a rich variety of transport phenomena as a function of charge density, drive, and pinning strength. For weak pinning, the system forms a defect-free crystal that depins elastically. When the pinning is stronger, a pinned glass phase appears that depins into a filamentary flow state, transitions at higher drives into a disordered flow phase, and finally forms a moving smectic. Within the filamentary flow phase, the conduction curves can show switching dynamics as well as negative differential conductivity in which switching events cause some flow channels to be blocked. The velocity noise in the filamentary flow regime exhibits narrow band characteristics due to the one-dimensional nature of the motion, while the moving smectic has narrow band velocity noise with a washboard frequency. In the disordered flow state, the noise power reaches a peak value and the noise has a 1/$\mathcal{f}$ character. Our transport results are consistent with recent experimental transport studies in systems where Wigner crystal states are believed to be occurring. Below the conduction threshold, we find that avalanches with a power-law size distribution appear when there are sudden local rearrangements of charges from one pinned configuration to another.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Deep learning Hamiltonians from disordered image data in quantum materials

The capabilities of image probe experiments are rapidly expanding, providing new information about quantum materials on unprecedented length- and timescales. Many such materials feature inhomogeneous electronic properties with intricate pattern formation on the observable surface. This rich spatial structure contains information about interactions, dimensionality, and disorder—a spatial encoding of the Hamiltonian driving the pattern formation. Image recognition techniques from machine learning are an excellent tool for interpreting information encoded in the spatial relationships in such images. Here, we develop a deep learning framework for using the rich information available in these spatial correlations in order to discover the underlying Hamiltonian driving the patterns. We first vet the method on a known case, scanning near-field optical microscopy on a thin film of V⁢O 2 . We then apply our trained convolutional neural network architecture to new optical microscope images of a different V⁢O 2 film as it goes through the metal-insulator transition. We find that a two-dimensional Hamiltonian with both interactions and random field disorder is required to explain the intricate, fractal intertwining of metal and insulator domains during the transition. This detailed knowledge about the underlying Hamiltonian paves the way for using the model to control the pattern formation via, e.g., tailored hysteresis protocols. Finally, we also introduce a distribution-based confidence measure on the results of a multilabel classifier, which does not rely on adversarial training. In addition, we propose a machine-learning-based criterion for diagnosing a physical system's proximity to criticality.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Quantum criticality and topology in non-equilibrium systems

A key goal of condensed matter physics research is to identify new phases of matter, and to understand the universal features of the phase transitions between them. In the past decade, physicists have uncovered a wealth of new phases with interesting surface properties, exemplified by the theoretical prediction and subsequent experimental discovery of topological insulators and superconductors. Traditional condensed matter systems are usually in a thermal equilibrium state and typically at very low temperature. Very recently, experimental advances have sparked interest in the non-equilibrium setting. Non-equilibrium systems can host new phases and phenomena with no equilibrium counterpart, and could also enable robust ways to build quantum memory devices to store and manipulate quantum information in a coherent manner. These phases and phenomena are inherently “dynamical”: they are described not by changes in the arrangement or structure of the constituent particles, but instead marked by sharp distinctions in how the particles move and exchange energy or quantum information. The discovery of robust non-equilibrium phases raises many fundamental questions: Can we develop a systematic theory of states of matter and of dynamical transitions between such states? How can such states be realized and probed experimentally? The main goal of this project was to explore the emergence of topological phases and quantum criticality (two cornerstones of modern condensed matter physics in equilibrium) in such non-equilibrium quantum systems. Specific goals included (1) using tensor networks to efficiently represent non-equilibrium states of matter and their phase transitions; (2) studying and designing new probes for periodically driven systems; and (3) developing analytic and numerical tools to analyze non-equilibrium topological phase transitions. Advances in these directions were achieved using novel techniques appropriate to study the non-equilibrium dynamics in many-body quantum systems combining strong interactions and randomness. Taken together, these results provide a new conceptual framework for understanding the emergence of quantum critical and topological properties in quantum systems far from thermal equilibrium.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Increasing Extractable Work in Small Qubit Landscapes

An interesting class of physical systems, including those associated with life, demonstrates the ability to hold thermalization at bay and perpetuate states of high free-energy compared to a local environment. In this work we study quantum systems with no external sources or sinks for energy, heat, work, or entropy that allow for high free-energy subsystems to form and persist. We initialize systems of qubits in mixed, uncorrelated states and evolve them subject to a conservation law. We find that four qubits make up the minimal system for which these restricted dynamics and initial conditions allow an increase in extractable work for a subsystem. On landscapes of eight co-evolving qubits, interacting in randomly selected subsystems at each step, we demonstrate that restricted connectivity and an inhomogeneous distribution of initial temperatures both lead to landscapes with longer intervals of increasing extractable work for individual qubits. We demonstrate the role of correlations that develop on the landscape in enabling a positive change in extractable work.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Multifrequency imaging radar polarimetry: Depolarisation of radar echoes at three wavelengths

It is shown that high resolution imaging radar polarimeters can describe depolarization effects in great detail by measuring the complete Stokes matrix for small regions on the Earth's surface, permitting to distinguish between coherent polarization transformation by the surface and diffuse interactions that randomize the polarization state of the received wave. Multiwavelength polarimeter observations of a variety of types of terrain, including images of the coherent and diffuse parts of the received signal are presented. The diffuse image, in particular, is highly indicative of small-scale surface roughness, an effect illustrated by analyzing a set of polarimeter images acquired over lava fields of varying roughness.

Zebker, H. A.↗

Probabilistic lifetime strength of aerospace materials via computational simulation

The results of a second year effort of a research program are presented. The research included development of methodology that provides probabilistic lifetime strength of aerospace materials via computational simulation. A probabilistic phenomenological constitutive relationship, in the form of a randomized multifactor interaction equation, is postulated for strength degradation of structural components of aerospace propulsion systems subjected to a number of effects of primitive variables. These primitive variables often originate in the environment and may include stress from loading, temperature, chemical, or radiation attack. This multifactor interaction constitutive equation is included in the computer program, PROMISS. Also included in the research is the development of methodology to calibrate the constitutive equation using actual experimental materials data together with the multiple linear regression of that data.

Boyce, Lola↗

Quantification of uncertainties in coupled material degradation processes - High temperature, fatigue and creep

This paper describes the development of methodology that provides for quantification of uncertainties in lifetime strength of aerospace materials subjected to a number of diverse effects. A probabilistic material degradation model, in the form of a randomized multifactor interaction equation, has been postulated for lifetime strength degradation of structural components of aerospace propulsion systems. The model includes effects that typically reduce lifetime strength and may include temperature, mechanical fatigue, creep and others. The paper also includes the analysis of experimental data from the open literature for Inconel 718. These data are used to provide an initial check for model validity, as well as for calibration of the model's empirical material constants. The model validity check and calibration is carried out for three effects, namely, high temperature, mechanical fatigue and creep.

Boyce, L.↗

Dynamics of charged particles in a Paul radio-frequency quadrupole trap

A molecular-dynamics simulation of hundreds of ions confined in a Paul trap has been performed. The simulation includes the trapped particles' micromotion and interparticle Coulomb interactions. A random walk in velocity was implemented to bring the secular motion to a given temperature which was numerically measured. When the coupling Gamma is large the ions from concentric shells which undergo a quadrupole oscillation at the RF frequency, while the ions within a shell form a 2D hexagonal lattice. Ion clouds at 5 mK show no RF heating for q(z) less than about 0.6, whereas rapid heating is seen for qz = 0.8.

Prestage, J. D.↗

Direct simulation of turbulent combustion

Understanding and modeling of turbulent combustion are key problems in the computation of numerous practical systems. Because of the lack of analytical theories in this field and of the difficulty of performing precise experiments, direct simulation appears to be one of the most attractive tools to use in addressing this problem. From Sep. 1989 - Sep. 1990, the following problems were studied using direct simulation but also experiments and theoretical models: (1) the influence of curvature on premixed flame fronts; (2) the construction of a model for the flame stretch based on direct simulation and multifractal analysis; and (3) the simulation of the interaction between random flow field and a flame front. The general objective was to improve knowledge of turbulent combustion but also to use this information for turbulent combustion models. The transfer of direct simulation results towards models is also in progress. A submodel to evaluate the flame stretch was derived from the present study and incorporated in the Coherent Flame model used in France for piston and aircraft engines.

Poinsot, Thierry J.↗

Probabilistic Material Strength Degradation Model for Inconel 718 Components Subjected to High Temperature, High-Cycle and Low-Cycle Mechanical Fatigue, Creep and Thermal Fatigue Effects

The development of methodology for a probabilistic material strength degradation is described. The probabilistic model, in the form of a postulated randomized multifactor equation, provides for quantification of uncertainty in the lifetime material strength of aerospace propulsion system components subjected to a number of diverse random effects. This model is embodied in the computer program entitled PROMISS, which can include up to eighteen different effects. Presently, the model includes five effects that typically reduce lifetime strength: high temperature, high-cycle mechanical fatigue, low-cycle mechanical fatigue, creep and thermal fatigue. Results, in the form of cumulative distribution functions, illustrated the sensitivity of lifetime strength to any current value of an effect. In addition, verification studies comparing predictions of high-cycle mechanical fatigue and high temperature effects with experiments are presented. Results from this limited verification study strongly supported that material degradation can be represented by randomized multifactor interaction models.

Bast, Callie C.↗

Fluorescence Studies of Protein Crystal Nucleation

We have postulated that, in the case of tetragonal chicken egg white lysozyme, crystal growth occurs by the addition of pre-critical nuclei sized n-mers that form in the bulk solution, and that the n-mer growth units were multiples of the tetrameric 4(sub 3) helical structure. These have the strongest intermolecular bonds in the crystal and are therefore likely to be the first species formed. High resolution AFM studies provide strong supporting evidence for this model, but the data also suggest that the actual species in solution may not be identical in structure to that found in the crystal. We are using fluorescence resonance energy transfer (FRET) to study the initial solution phase self-assembly process, using covalent fluorescent derivatives which crystallize in the characteristic P4(sub 3)2(sub 1)2(sub 1) space group. FRET studies are being carried out between the cascade blue (CB-lys, donor, Ex(sub max) 366 nm, Em 420 nm) and lucifer yellow (LY-lys, acceptor, Ex(sub max) 430 nm, Em 528 nm) asp101 derivatives. The estimated R(sub 0) for this probe pair, the distance where 50% of the donor energy is transferred to the acceptor, is approx. 1.2 nm, compared to 2.2 nm between the side chain carboxyls of adjacent asp101's in the crystalline 4(sub 3) helix. The short donor lifetime of 2.80 ns (chi(sup 2) = 0.644), coupled with the large average distances between the molecules (greater than or equal to 50 nm) in solution, ensure that any energy transfer observed is not due to random diffusive interactions. Lifetime data show that CB-lys has a single lifetime when it is the only species in solution. Similarly, LY-lys also exhibits a single lifetime of 4.63 ns (chi(sup 2) = 0.42) when alone in solution. Addition of LY-lys to CB-lys results in the appearance of a third lifetime component of 0.348ns for the CB-lys. The fractional intensities of the different species present can be used to estimate the distribution of monomer and n-mers in solution. The self-association process is a function of the protein concentration relative to the saturation concentration, and observing it in dilute solution (conc. less than or equal to 10(exp -5)M) requires that the experiments be performed under low solubility conditions, i.e., low temperatures and high salt concentrations. Data from preliminary steady state FRET studies with N-terminal bound pyrene acetic acid (PAA-lys, donor, Ex 340 nm, Em 376 nm) and asp101 LY-lys as an acceptor showed a consistent trend of decreasing donor fluorescence intensity with increasing total protein concentration. The FRET data have been obtained at pH 4.6, 0.1M NaAc buffer, at 5 and 7% NaCl, 4 C. The corresponding C(sub sat) values are 0.471 and 0.362 mg/ml (approx. 3.3 and approx. 2.5 x 10(exp -5)M respectively). The donor fluorescence decrease is more pronounced at7% NaCl, consistent with the expected increased intermolecular interactions at higher salt concentrations as reflected in the lower solubility. Results from these and other ongoing studies will be discussed in conjunction with an emerging model for how tetragonal lysozyme crystals nucleate and the relevance of that model to other proteins.

Pusey, Marc↗

Fluorescence Studies of Protein Crystal Nucleation

One of the most powerful and versatile methods for studying molecules in solution is fluorescence. Crystallization typically takes place in a concentrated solution environment, whereas fluorescence typically has an upper concentration limit of approximately 1 x 10(exp -5)M, thus intrinsic fluorescence cannot be employed, but a fluorescent probe must be added to a sub population of the molecules. However the fluorescent species cannot interfere with the self-assembly process. This can be achieved with macromolecules, where fluorescent probes can be covalently attached to a sub population of molecules that are subsequently used to track the system as a whole. We are using fluorescence resonance energy transfer (FRET) to study the initial solution phase self-assembly process of tetragonal lysozyme crystal nucleation, using covalent fluorescent derivatives which crystallize in the characteristic P432121 space group. FRET studies are being carried out between cascade blue (CB-lys, donor, Ex 376 nm, Em 420 nm) and lucifer yellow (LY-lys, acceptor, Ex 425 nm, Em 520 nm) asp101 derivatives. The estimated R0 for this probe pair, the distance where 50% of the donor energy is transferred to the acceptor, is approximately 1.2 nm, compared to 2.2 nm between the side chain carboxyls of adjacent asp101's in the crystalline 43 helix. The short CB-lys lifetime (approximately 5 ns), coupled with the large average distances between the molecules ((sup 3) 50 nm) in solution, ensure that any energy transfer observed is not due to random diffusive interactions. Addition of LY-lys to CB-lys results in the appearance of a second, shorter lifetime (approximately 0.2 ns). Results from these and other ongoing studies will be discussed in conjunction with a model for how tetragonal lysozyme crystals nucleate and grow, and the relevance of that model to microgravity protein crystal growth

Pusey, Marc L.↗

Cloud Macroscopic Organization: Order Emerging from Randomness

Clouds play a central role in many aspects of the climate system and their forms and shapes are remarkably diverse. Appropriate representation of clouds in climate models is a major challenge because cloud processes span at least eight orders of magnitude in spatial scales. Here we show that there exists order in cloud size distribution of low-level clouds, and that it follows a power-law distribution with exponent gamma close to 2. gamma is insensitive to yearly variations in environmental conditions, but has regional variations and land-ocean contrasts. More importantly, we demonstrate this self-organizing behavior of clouds emerges naturally from a complex network model with simple, physical organizing principles: random clumping and merging. We also demonstrate symmetry between clear and cloudy skies in terms of macroscopic organization because of similar fundamental underlying organizing principles. The order in the apparently complex cloud-clear field thus has its root in random local interactions. Studying cloud organization with complex network models is an attractive new approach that has wide applications in climate science. We also propose a concept of cloud statistic mechanics approach. This approach is fully complementary to deterministic models, and the two approaches provide a powerful framework to meet the challenge of representing clouds in our climate models when working in tandem.

Yuan, Tianle↗

Fibre intersections in a planar randomly oriented fibre composite

The interaction of fibers in a randomly oriented fiber composite is a key factor in determining the mechanical properties of some composites. A theoretical model is presented by means of which values of the mean and the variance of fiber intersections in a planar randomly oriented fiber composite are predicted. These predictions are compared with the mean and variance obtained from a computer simulation of the fiber intersection process.

Williams, J. H., Jr.↗

An SYK-inspired model with density–density interactions: Spectral & wave function statistics, Green’s function and phase diagram

The Sachdev–Ye–Kitaev (SYK) model is a rare example of a strongly-interacting system that is analytically tractable. Tractability arises because the model is largely structureless by design and therefore artificial: while the interaction is restricted to two-body terms, interaction matrix elements are “randomized” and therefore the corresponding interaction operator does not commute with the local density. Unlike conventional density–density-type interactions, the SYK-interaction is, in this sense, not integrable. We here investigate a variant of the (complex) SYK model, which restores this integrability. It features a randomized single-body term and a density–density-type interaction. We present numerical investigations suggesting that the model exhibits two integrable phases separated by several intermediate phases including a chaotic one. The chaotic phase carries several characteristic SYK-signatures including in the spectral statistics and the frequency scaling of the Green’s function and therefore should be adiabatically connected to the non-Fermi liquid phase of the original SYK model. Thus, our model Hamiltonian provides a bridge from the SYK-model towards microscopic realism.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗